Plant-wide optimization and control of an industrial diesel hydro-processing plant

Aydın, Erdal; Arkun, Yaman; Is, Gamze; Mutlu, Mustafa; Dikbas, Mine

doi:10.1016/j.compchemeng.2016.01.016

Cited by 8 publications

(6 citation statements)

References 17 publications

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“…There are significant contributions for plant-wide control and optimization, especially in the chemical industry, while only a few focus on bioprocesses. For example, Aydin et al [66] implemented a plant-wide optimization and control strategy to an industrial diesel hydro-processing process. Jeppsson et al [67] developed a plant-wide control framework for performance evaluation of wastewater treatment to develop a benchmark simulation model.…”

Section: Plant-wide Optimizationmentioning

confidence: 99%

Digital Twin in biomanufacturing: challenges and opportunities towards its implementation

Udugama

López

Gargalo

et al. 2021

Syst Microbiol and Biomanuf

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The domain of industrial biomanufacturing is enthusiastically embracing the concept of Digital Twin, owing to its promises of increased process efficiency and resource utilisation. However, Digital Twin in biomanufacturing is not yet clearly defined and this sector of the industry is falling behind the others in terms of its implementation. On the other hand, some of the benefits of Digital Twin seem to overlap with the more established practices of process control and optimization, and the term is vaguely used in different scenarios. In an attempt to clarify this issue, we investigate this overlap for the specific case of fermentation operation, a central step in many biomanufacturing processes. Based on this investigation, a framework built upon a five-step pathway starting from a basic steady-state process model is proposed to develop a fully-fledged Digital Twin. For demonstration purposes, the framework is applied to a bench-scale second-generation ethanol fermentation process as a case study. It is proposed that the success or failure of a fully-fledged Digital Twin implementation is determined by key factors that comprise the role of modelling, human operator actions, and other propositions of economic value.

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Section: Plant-wide Optimizationmentioning

confidence: 99%

Digital Twin in biomanufacturing: challenges and opportunities towards its implementation

Udugama

López

Gargalo

et al. 2021

Syst Microbiol and Biomanuf

View full text Add to dashboard Cite

show abstract

“…For more details about the distillation process, refer to the previous literature. − Obviously, it is the reaction system rather than the fractionation system that determines the distribution of end products primarily. The dynamic modeling for the crucial reaction system has received more and more attention, such as the classical Stangeland model, the product-oriented model, the discrete lumped models, , and the continuous lumped models. ,,− Among the existing methods, continuous lumping has become extremely popular in recent years. With the distillation curves of inlet reactants and outlet products, it is not difficult to set up equilibrium equations for the reaction system using dynamics and thermodynamics laws.…”

Section: Distillation Curve Reconstruction and Feature Parameter Extr...mentioning

confidence: 99%

“…However, it is difficult to get samples from the internal reaction system during its running time. Therefore, in most of the previous works, , commercial software was coincidentally employed to calculate those key but unsampled streams. Concretely, distillation data of the intermediate products were estimated by the oil manager of Aspen HYSYS, with some available information of the end products.…”

Section: Distillation Curve Reconstruction and Feature Parameter Extr...mentioning

confidence: 99%

Asymmetric Probability Distribution Function-Based Distillation Curve Reconstruction and Feature Extraction for Industrial Oil-Refining Processes

2020

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A distillation curve is an essential property for petroleum. Its features are beneficial for the modeling and optimization of oil-refining processes. To capture these features with a small number of parameters, an asymmetric probability distribution function-based distillation curve reconstruction and feature extraction method is proposed for the industrial oil-refining process. In our research, the expressive power of several frequently used probability distribution functions are first tested with some available distillation data. According to the statistics, the Kumaraswamy distribution function, one of the asymmetric probability distribution functions with four parameters, is identified as the best. Because not all distillation data are directly obtainable in the industry, the total probability theory-based data synthesis technique is adopted to estimate the key distillation points of unsampled streams, especially for the unmeasurable intermediate products at the outlet of a reaction system. Along with the distillation curve reconstruction, features of the synthetic distillation data are extracted by optimizing the parameters of the Kumaraswamy distribution function using the state transition algorithm. Industrial experiments were carried out to demonstrate the effectiveness of our proposal.

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“…Aydin et al demonstrated a two-layer MPC model on a hydrotreatment plant [99]. In the upper level, an economic MPC was used with long sampling time and in the lower level two decoupled MPCs, one for feed blending and another for temperature control, with much shorter sampling time were employed.…”

Section: Optimization and Controlmentioning

confidence: 99%

Hydrocracking: A Perspective towards Digitalization

2020

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In a world of fast technological advancements, it is increasingly important to see how hydrocracking applications can benefit from and adapt to digitalization. A review of hydrocracking processes from the perspective of modeling and characterization methods is presented next to an investigation on digitalization trends. Both physics-based and data-based models are discussed according to their scope of use, needs, and capabilities based on open literature. Discrete and continuous lumping, structure-oriented lumping, and single event micro-kinetic models are reported as well as artificial neural networks, convolutional neural networks, and surrogate models. Infrared, near-infrared, ultra-violet and Raman spectroscopic methods are given with their examples for the characterization of feed or product streams of hydrocracking processes regarding boiling point curve, API, SARA, sulfur, nitrogen and metal content. The critical points to consider while modeling the system and the soft sensor are reported as well as the problems to be addressed. Optimization, control, and diagnostics applications are presented together with suggested future directions of interdisciplinary studies. The links required between the models, soft sensors, optimization, control, and diagnostics are suggested to achieve the automation goals and, therefore, a sustainable operation.

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Plant-wide optimization and control of an industrial diesel hydro-processing plant

Cited by 8 publications

References 17 publications

Digital Twin in biomanufacturing: challenges and opportunities towards its implementation

Digital Twin in biomanufacturing: challenges and opportunities towards its implementation

Asymmetric Probability Distribution Function-Based Distillation Curve Reconstruction and Feature Extraction for Industrial Oil-Refining Processes

Hydrocracking: A Perspective towards Digitalization

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